Context-Aware Apps: How to Super Charge Your Customer Engagement

Consider the Challenges

Step Five: Get acquainted with the technical challenges and considerations.

CAAs are the next generation of intelligent apps, and while they go beyond personalized, location-based messaging, it is not a bad idea to begin building context data by linking user profiles and demographics with past activities, app behaviors and purchases as a starting point. But there are a few things to keep in mind:

While lots of effort should go into collecting user information, in the case of privacy-sensitive applications such as HIPAA-compliant medical apps, the user can be de-identified while keeping a record or token that allows the app to still learn personal preferences and provide contextual interactions.

A smartphone's sensors can be used to receive additional context data. The more context data an app can collect – i.e., Big Data – the more information can be provided to the user. But in order for this data to be useful to the app and the user, the data usually needs to be analyzed in real-time, or risk becoming stale and irrelevant. A Big Data architecture may be required so the app can return useful information quickly.

Inferred information from context data is another issue to consider in terms of accuracy – what if the information derived from context is so far from reality that the app behaves unexpectedly? What can be done to mitigate such an event, and achieve a reasonable user experience under such risk?

Developing an application that is used frequently by a specific audience requires a rigorous design and development process. This includes defining the app's goals and objectives, determining its features and functionality, designing a user experience that is both engaging and delightful and building the underlying architecture and analytics that will support the functions of the app — even before writing the first line of code.

Mobile devices are arguably the best way to deliver messages at the right time and place given their always-on nature. So, when building a mobile app with the goal of being useful and engaging, making it a context-aware app is ideal.

Context-aware applications, or CAAs, are the next generation of intelligent mobile applications. When allowed by their users, these apps use contextual data: from historical information about the user's demographics and behavior profiles to data about the current surroundings obtained through the smartphone's microphones, accelerometers, gyroscope, cameras and other sensors. Combining these inputs with the current time and location via GPS, CAAs paint a picture about the user's immediate context, and use the information to deliver tailored experiences in the form of timely, relevant and appropriate information, notifications and/or functionality. As compared to other apps, CAAs sustain a user's attention and are more effective at influencing or changing behavior.

But where do you start? In this slideshow, Gary Rozal, Ph.D., vice president, Analytics at Mobiquity, has identified five steps for developing the next evolution of mobile apps.

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